Volume 7 Issue 5
Nov.  2018
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Article Navigation >  Journal of Radars  > 2018  >  7(5): 575-584
XIA Deping, ZHANG Liang, WU Tao, et al. A multiple interference suppression algorithm based on airborne bistatic polarization radar[J]. Journal of Radars, 2022, 11(3): 399–407. doi: 10.12000/JR21212
Citation: Luo Ying, Gong Yishuai, Chen Yijun, Zhang Qun. Multi-target Micro-motion Feature Extraction Based on Tracking Pulses in MIMO Radar[J]. Journal of Radars, 2018, 7(5): 575-584. doi: 10.12000/JR18035
shu

Multi-target Micro-motion Feature Extraction Based on Tracking Pulses in MIMO Radar

DOI: 10.12000/JR18035
  • ①.

    Institute of Information and Navigation, Air Force Engineering University, Xi’an 710077, China

  • ②.

    Troop of No. 95561, PLA, Lasa 850000, China

  • ③.

    College of Information Engineering, Engineering University of CAPF, Xi’an 710086, China

Funds:  The National Natural Science Foundation of China (61571457, 61631019)
  • Received Date: 2018-04-25
  • Rev Recd Date: 2018-06-02
  • Publish Date: 2018-10-28
    Abstract
  • The micro-motion feature is one of the important characteristic information of spatial target recognition. However, the existing multifunctional Multi-Input Multi-Output (MIMO) radar usually has to allocate a large number of continuous time resources for target micro-motion feature extraction after target searching and tracking, which leads to a low real-time performance of target recognition and poor overall performance of radar system. To solve this problem, this paper presents a multi-target micro-motion feature extraction method for MIMO radar based on tracking pulses. First, according to the azimuth information of each target, the MIMO radar transmitting waveform is designed, and the tracking pulses are transmitted simultaneously for targets with different directions. On this basis, by considering the micro-motion feature extraction performance and the target tracking performance synthetically, the transmission time series of the tracking pulses are optimized. Finally, the narrowband tracking pulses are directly used to simultaneously extract the micro-motion features of the targets in different directions, which makes it no longer necessary to allocate additional radar resources for target feature extraction. Consequently, the real-time recognition performance and the working efficiency of radar are improved significantly. Simulations demonstrate that when the signal-to-noise ratio is larger than –10 dB, the micro-motion features of multi-targets can be extracted accurately, which verifies the effectiveness and robustness of the proposed method.

     

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    • References(18)
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